search for: quandt

Displaying 4 results from an estimated 4 matches for "quandt".

Did you mean: quand
2009 Sep 18
1
some irritation with heteroskedasticity testing
...eve, it isn't really increasing... 2. further I ran the following tests bptest (studentized and non-studentized), gqtest, ncv.test with the following results: ncv: Non-constant Variance Score Test Variance formula: ~ fitted.values Chisquare = 13.87429 Df = 1 p = 0.00194580 Goldfeld-Quandt test data: reg GQ = 1.7092, df1 = 327, df2 = 327, p-value = 7.93e-07 studentized Breusch-Pagan test data: reg BP = 15.8291, df = 23, p-value = 0.92 Breusch-Pagan test data: reg BP = 377.5604, df = 23, p-value < 2.8e-18 bptest and gq.test sport pretty straight forward examples saying the...
2006 Sep 29
6
List-manipulation
Hi, Sorry for the question, I know it should be basic knowledge but I'm struggling for two hours now. How do I select only the first entry of each list member and ignore the rest? So for > $"121_at" > -113691170 > $"1255_g_at" > 42231151 > $"1316_at" > 35472685 35472588 > $"1320_at" > -88003869
2009 May 12
0
R^2 extraction and autocorrelation/heterokedasticity on TSLS regression
...ar multiple regression on annually data which go from 1971 to 1997. After performing the TSLS regression, I tried to extract the R squared value using “output$r.squared” function and to perform autocorrelation (Durbin Watson and Breush Godfrey) and heterokedasticity tests (Breush-pagan and Goldfeld Quandt)  but I have errors messages. More specifically, this is function that I write to R and below its response : for R^2 : > output$r.squared NULL for heterokedasticity tests : >bptest(reg1) Error in terms.default(formula) : no terms component and for autocorrelation test, when I try : durbin.wat...
2005 Jan 25
1
Threshhold Models in gnlm
Hello, I am interested in fitting a generalized nonlinear regression (gnlr) model with negative binomial errors. I have found Jim Lindsay's package that will do gnlr, but I have having trouble with the particular model I am interested in fitting. It is a threshhold model, where below a certain value of one of the parameters being fitted, the model changes. Here is a sample: Cones: